Job description
Job Function, Roles & Responsibilities: • Lead strategic initiatives and own the practice for Edge AI/ML, data pipelines, and intelligent embedded systems • Define and build the competency roadmap for machine learning, deep learning, model deployment, and real-time inferencing on edge platforms • Oversee data creation — including data collection, dataset curation, annotation, cleaning, augmentation, and synthetic data generation • Champion use cases involving sensor fusion, combining data from multiple sources (vision, IMU, radar, audio, etc.) to create robust, efficient, and context-aware edge intelligence solutions • Drive edge analytics and on-device learning across verticals such as Industrial Automation, Medical Devices, Automotive, and Smart Consumer Electronics • Collaborate with global customers to gather requirements, architect solutions, track project delivery, and ensure alignment with business objectives • Support business development with presales solutioning, proposal writing, and effort estimation • Drive internal capability building through mentoring, training, and competency development ________________________________________ Experience: 10+ years in embedded systems, AI/ML, and data engineering, with a strong focus on edge intelligence and real-time systems. ________________________________________ Area of Expertise: • Proven expertise in deploying ML/DL models on edge devices (NVIDIA Jetson, NXP i.MX, Qualcomm QCS, TI Sitara, etc.) • Strong knowledge of data workflows: dataset generation, manual/automated annotation, data cleaning, augmentation, and synthetic data creation • Deep understanding of sensor fusion techniques combining inputs from vision, audio, IMU, radar, LIDAR, and other sources to improve model accuracy and efficiency • Experience in model optimization using TensorRT, ONNX, OpenVINO, TFLite, and TVM • Hands-on with TensorFlow, PyTorch, scikit-learn, and signal/image processing techniques • Proficient in designing for real-time inference on resource-constrained platforms • Exposure to AI accelerators, NPUs, DSPs, and hybrid SoC environments; must have exposure to NVIDIA SoC & Tools • Presales, account engagement, and solutioning experience with North American or European clients ________________________________________ Nice to Have: • Cloud-edge integration using AWS Greengrass, Azure ...
